In [1]:
import plotly.offline as pyo

from plotly.graph_objs import *

import chart_studio.plotly as py

import pandas as pd
from pandas import DataFrame
In [2]:
pyo.offline.init_notebook_mode()
In [4]:
stocks = py.get_figure("https://plotly.com/~rmuir/162/stock-closing-prices-for-apple-in-2012/")
In [5]:
stocks
In [6]:
other_stocks = py.get_figure('rmuir', 162)
In [7]:
other_stocks
In [8]:
pyo.iplot(stocks)
In [9]:
stocks['layout']['yaxis'].update({'range' : [0, 1000]})
pyo.iplot(stocks)
In [10]:
maximum = max(stocks['data'][0]['y'])
maximum
Out[10]:
702.100021
In [11]:
stocks['layout']['yaxis'].update({'range' : [0, maximum * 1.05]})
pyo.iplot(stocks)
In [12]:
df = pd.read_csv(r"../Data/BoEBaseRate.csv")
In [13]:
df.head(5)
Out[13]:
Unnamed: 0 VALUE DATE
0 0 11.5 1975-01-02
1 1 11.5 1975-01-03
2 2 11.5 1975-01-06
3 3 11.5 1975-01-07
4 4 11.5 1975-01-08
In [14]:
df.max()
Out[14]:
Unnamed: 0         10485
VALUE               17.0
DATE          2016-06-23
dtype: object
In [16]:
df['strDate'] = pd.to_datetime(df['DATE'], format="%Y/%m/%d")
df.head()
Out[16]:
Unnamed: 0 VALUE DATE strDate
0 0 11.5 1975-01-02 1975-01-02
1 1 11.5 1975-01-03 1975-01-03
2 2 11.5 1975-01-06 1975-01-06
3 3 11.5 1975-01-07 1975-01-07
4 4 11.5 1975-01-08 1975-01-08
In [17]:
df.max()
Out[17]:
Unnamed: 0                  10485
VALUE                        17.0
DATE                   2016-06-23
strDate       2016-06-23 00:00:00
dtype: object
In [18]:
df['VALUE'].max()
Out[18]:
17.0
In [19]:
df.min()
Out[19]:
Unnamed: 0                      0
VALUE                         0.5
DATE                   1975-01-02
strDate       1975-01-02 00:00:00
dtype: object
In [20]:
df['VALUE'].min()
Out[20]:
0.5
In [ ]: